Figure 1 (Infection)

Fig 1bcd

Survival Curves

Fig1b

Fig1c

Fig1d

Fig 1e

Supp Figure 1 (Viral load)

Scatterplots vs 3 groups

week 1 post infection

week 2 post infection

week 4 post infection

week 6 post infection

week 8 post infection

week 10 post infection

week 12 post infection

Figure 2 (Functional Assays in Blood)

Fig2acefghjk

Fig2a

Fig2c

Fig2e

Fig2f

Fig2g

Fig2h

Fig2j

Fig2k

Fig2b

Plasma_peptide26gp120_antibody_response__WkPost vs Plasma_AvidityScore_cV2gp120__WkPost

Fig2di

Fig2d

Fig2i

Fig2l

WkPostAndChange

ALUM

14 up and 2 down pairs with p < 0.05

ALFQA

17 up and 0 down pairs with p < 0.05

alluvial (0.05)

Supp Figure 2 (Functional Assays in Blood)

SuppFig2abcdefhi

SuppFig2a

SuppFig2b

SuppFig2c

SuppFig2d

SuppFig2e

SuppFig2f

SuppFig2h

SuppFig2i

SuppFig2gjkl

SuppFig2g

Plasma_ADCC_Killing__WkPost vs Plasma_gp120_antibody_titers__WkPost

SuppFig2j

Plasma_ADCP_SIVgp120dV1__Change vs Plasma_ADNP_SIVgp120dV1__Change

SuppFig2k

Plasma_Trogocytosis_dV1gp120__Change vs Plasma_ADNP_SIVgp120dV1__Change

SuppFig2l

Plasma_AvidityScore_dV1M766gp120__WkPost vs Plasma_ADNP_SIVgp120dV1__Change

Figure 3 (RM)

Fig3aeh

Fig3a

Fig3e

Fig3h

Fig3b

PBMCs_PctCD14_efferocytes__WkPost vs RectMucosa_CD73posCD163posMacrophages__Change

Fig3cfg

Fig3c

Fig3f

Fig3g

Fig3di

Fig3d

Fig3i

Fig3j

WkPostAndChange

ALUM

24 up and 3 down pairs with p < 0.05

ALFQA

13 up and 1 down pairs with p < 0.05

alluvial (0.05)

Supp Figure 3 (FACS scheme)

FACS scheme

Supp Figure 4 (RM)

SuppFig4bdehi

SuppFig4b

SuppFig4d

SuppFig4e

SuppFig4h

SuppFig4i

SuppFig4cfklmno

SuppFig4c

RectMucosa_CD73posCD163posMacrophages__Change vs Vaginal_secretions_dV1gp120_antibody_titers__WkPost

SuppFig4f

RectMucosa_CD73posCD163posMacrophages__Change vs RectMucosa_CD73posDC10__Change

SuppFig4k

RectMucosa_DC10__Change vs RectMucosa_NKp44__WkPost

SuppFig4l

RectMucosa_CD163posMacrophages__Change vs RectMucosa_NKp44__Change

SuppFig4m

RectMucosa_CD163posMacrophages__Change vs RectMucosa_NKp44negNKG2Aneg_PMA_IFNg__Change

SuppFig4n

RectMucosa_CD73posCD163posMacrophages__WkPost vs RectMucosa_NKp44negNKG2Aneg_PMA_IFNg__WkPost

SuppFig4o

Plasma_ADCC_Killing__WkPost vs RectMucosa_NKp44__Change

SuppFig4j

SuppFig4j

Figure 4 (Plasma cytokines)

Fig4a

ellipse = 95 % normal probability

top 5 loadings per PC displayed

17 ALUM + 12 ALFQA animals in PCA

Fig4b

ellipse = 95 % normal probability

top 5 loadings per PC displayed

12 ALUM + 12 ALFQA animals in PCA

Fig4c

x-axis: log10(abs(MW estimate x100)) x sign of MW estimate

MW estimate = median of outer differences

outer differences = difference between all pairs of values in group1 - group2, e.g. for A = a1, a2 and B = b1, b2; then the outer differences would be: a1-b1, a2-b1, a1-b2, a2-b2. And the MW estimate is the median of these deltas. For MW estimate > 0, ALFQA > ALUM; and for MW estmate < 0, ALFQA < ALUM

x100 = to shift all estimates > 1 (or < -1) so that the log10 does not transform values -1 < x < 1; thus for a MW estimate of 0.01 (the smallest magnitude estimate) –> log10(0.01 x100) = 0

Fig4d

x-axis: log10(abs(MW estimate x100)) x sign of MW estimate

MW estimate = median of outer differences

outer differences = difference between all pairs of values in group1 - group2, e.g. for A = a1, a2 and B = b1, b2; then the outer differences would be: a1-b1, a2-b1, a1-b2, a2-b2. And the MW estimate is the median of these deltas. For MW estimate > 0, ALFQA > ALUM; and for MW estmate < 0, ALFQA < ALUM

x100 = to shift all estimates > 1 (or < -1) so that the log10 does not transform values -1 < x < 1; thus for a MW estimate of 0.01 (the smallest magnitude estimate) –> log10(0.01 x100) = 0

Fig4e

baseline same assays, without Baseline

Fig4fghijk

Fig4f

Fig4g

Fig4h

Fig4i

Fig4j

Fig4k

Supp Figure 5 (Plasma cytokines)

SuppFig5a

ellipse = 95 % normal probability

top 5 loadings per PC displayed

12 ALUM + 12 ALFQA animals in PCA

SuppFig5b

x-axis: log10(abs(MW estimate x100)) x sign of MW estimate

MW estimate = median of outer differences

outer differences = difference between all pairs of values in group1 - group2, e.g. for A = a1, a2 and B = b1, b2; then the outer differences would be: a1-b1, a2-b1, a1-b2, a2-b2. And the MW estimate is the median of these deltas. For MW estimate > 0, ALFQA > ALUM; and for MW estmate < 0, ALFQA < ALUM

x100 = to shift all estimates > 1 (or < -1) so that the log10 does not transform values -1 < x < 1; thus for a MW estimate of 0.01 (the smallest magnitude estimate) –> log10(0.01 x100) = 0

SuppFig5c

Baseline diff only

SuppFig5d

SuppFig5e

Figure 5 (Plasma cytokines)

Fig5a

Baseline

ALUM

2 up and 0 down pairs with p < 0.001

ALFQA

6 up and 0 down pairs with p < 0.001

alluvial (0.001)

wk12_24h

ALUM

8 up and 0 down pairs with p < 0.001

ALFQA

8 up and 0 down pairs with p < 0.001

alluvial (0.001)

wk13

ALUM

1 up and 0 down pairs with p < 0.001

ALFQA

10 up and 0 down pairs with p < 0.001

alluvial (0.001)

Fig5b

For IPA (see methods)

Fig5c

For IPA (see methods)

Supp Figure 6 (Pathway analysis)

SuppFig6a

For IPA (see methods)

SuppFig6b

For IPA (see methods)

Figure 6 (Plasma cytokines & Summary)

Fig 6a

Fig6bd

Fig6b

Fig6d

Fig6c

RectMucosa_DC10__Change vs LTA__wk13

Fig 6e

Summary of variables different ALFQA vs Alum, associations with TOA

Supp Figure 7 (Plasma cytokines & summary)

Supp Fig7a

Supp Fig7b

SuppFig7cde

SuppFig7c

RectMucosa_DC10__Change vs MMP12__wk12_24h

SuppFig7d

RectMucosa_DC10__Change vs CCL13__wk12_24h

SuppFig7e

RectMucosa_DC10__Change vs VEGFA__wk12_24h

Supp Fig7f

ALUM

ALFQA

Supp Figure 8 (Plasma cytokines & summary)

SuppFig8abc

SuppFig8a

SuppFig8b

SuppFig8c

SuppFig8d

CXCL8__wk13 vs EGF__wk13

Supp Fig8e

ALUM

ALFQA

Data tables

Stats

Mann-Whitney/Wilcoxon test between groups at each timepoint

Spearman correlation between TOA and assays, or among assays

Excel spreadsheet of stats

Session info

## R version 4.4.1 (2024-06-14)
## Platform: aarch64-apple-darwin20
## Running under: macOS 15.5
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## time zone: America/New_York
## tzcode source: internal
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] igraph_2.1.4             rstatix_0.7.2            ggalluvial_0.12.5       
##  [4] dendextend_1.17.1        dendsort_0.3.4           strex_2.0.1             
##  [7] ggbiplot_0.55            scales_1.4.0             plyr_1.8.9              
## [10] corrplot_0.95            statmod_1.5.0            variancePartition_1.34.0
## [13] BiocParallel_1.38.0      edgeR_4.2.2              limma_3.60.6            
## [16] lmerTest_3.1-3           lme4_1.1-35.5            Matrix_1.7-0            
## [19] EnhancedVolcano_1.22.0   geepack_1.3.10           filesstrings_3.4.0      
## [22] colorspace_2.1-1         RColorBrewer_1.1-3       janitor_2.2.0           
## [25] officer_0.6.6            PCAtools_2.16.0          flextable_0.9.6         
## [28] ggplotify_0.1.2          plotly_4.10.4            ggrepel_0.9.6           
## [31] ggbeeswarm_0.7.2         DT_0.33                  gridExtra_2.3           
## [34] gtsummary_1.7.2          kableExtra_1.4.0         broom_1.0.7             
## [37] knitr_1.50               OlinkAnalyze_3.7.0       ggsurvfit_1.0.0         
## [40] enrichR_3.2              eulerr_7.0.2             survival_3.6-4          
## [43] ggpubr_0.6.0             pheatmap_1.0.12          cowplot_1.1.3           
## [46] lubridate_1.9.4          forcats_1.0.0            stringr_1.5.1           
## [49] dplyr_1.1.4              purrr_1.0.4              readr_2.1.5             
## [52] tidyr_1.3.1              tibble_3.2.1             ggplot2_3.5.2           
## [55] tidyverse_2.0.0          readxl_1.4.3             openxlsx_4.2.5.2        
## 
## loaded via a namespace (and not attached):
##   [1] splines_4.4.1             later_1.4.2              
##   [3] bitops_1.0-9              cellranger_1.1.0         
##   [5] lifecycle_1.0.4           Rdpack_2.6               
##   [7] lattice_0.22-6            MASS_7.3-60.2            
##   [9] crosstalk_1.2.1           backports_1.5.0          
##  [11] magrittr_2.0.3            sass_0.4.10              
##  [13] rmarkdown_2.29            jquerylib_0.1.4          
##  [15] yaml_2.3.10               httpuv_1.6.16            
##  [17] zip_2.3.2                 askpass_1.2.1            
##  [19] minqa_1.2.8               multcomp_1.4-25          
##  [21] abind_1.4-8               zlibbioc_1.50.0          
##  [23] EnvStats_2.8.1            BiocGenerics_0.50.0      
##  [25] yulab.utils_0.1.4         WriteXLS_6.5.0           
##  [27] TH.data_1.1-2             sandwich_3.1-0           
##  [29] gdtools_0.3.7             IRanges_2.38.1           
##  [31] S4Vectors_0.42.1          pbkrtest_0.5.3           
##  [33] irlba_2.3.5.1             crul_1.4.2               
##  [35] dqrng_0.4.1               svglite_2.1.3            
##  [37] DelayedMatrixStats_1.26.0 codetools_0.2-20         
##  [39] DelayedArray_0.30.1       xml2_1.3.8               
##  [41] tidyselect_1.2.1          httpcode_0.3.0           
##  [43] farver_2.1.2              viridis_0.6.5            
##  [45] ScaledMatrix_1.12.0       matrixStats_1.5.0        
##  [47] stats4_4.4.1              broom.helpers_1.15.0     
##  [49] jsonlite_2.0.0            Formula_1.2-5            
##  [51] iterators_1.0.14          emmeans_1.10.1           
##  [53] systemfonts_1.2.3         tools_4.4.1              
##  [55] ragg_1.4.0                Rcpp_1.0.14              
##  [57] glue_1.8.0                SparseArray_1.4.8        
##  [59] mgcv_1.9-1                xfun_0.52                
##  [61] MatrixGenerics_1.16.0     withr_3.0.2              
##  [63] numDeriv_2016.8-1.1       fastmap_1.2.0            
##  [65] boot_1.3-30               openssl_2.3.2            
##  [67] caTools_1.18.3            digest_0.6.37            
##  [69] rsvd_1.0.5                timechange_0.3.0         
##  [71] R6_2.6.1                  mime_0.13                
##  [73] gridGraphics_0.5-1        estimability_1.5         
##  [75] textshaping_1.0.1         gtools_3.9.5             
##  [77] dichromat_2.0-0.1         RhpcBLASctl_0.23-42      
##  [79] generics_0.1.4            corpcor_1.6.10           
##  [81] fontLiberation_0.1.0      data.table_1.17.2        
##  [83] httr_1.4.7                htmlwidgets_1.6.4        
##  [85] S4Arrays_1.4.1            pkgconfig_2.0.3          
##  [87] gtable_0.3.6              XVector_0.44.0           
##  [89] remaCor_0.0.18            htmltools_0.5.8.1        
##  [91] fontBitstreamVera_0.1.1   carData_3.0-5            
##  [93] Biobase_2.64.0            fANCOVA_0.6-1            
##  [95] snakecase_0.11.1          rstudioapi_0.17.1        
##  [97] tzdb_0.5.0                reshape2_1.4.4           
##  [99] rjson_0.2.21              uuid_1.2-1               
## [101] checkmate_2.3.2           coda_0.19-4.1            
## [103] nlme_3.1-164              curl_6.2.2               
## [105] nloptr_2.1.1              cachem_1.1.0             
## [107] zoo_1.8-14                KernSmooth_2.23-24       
## [109] parallel_4.4.1            vipor_0.4.7              
## [111] pillar_1.10.2             vctrs_0.6.5              
## [113] gplots_3.2.0              promises_1.3.2           
## [115] car_3.1-3                 BiocSingular_1.20.0      
## [117] beachmat_2.20.0           xtable_1.8-4             
## [119] beeswarm_0.4.0            evaluate_1.0.3           
## [121] locfit_1.5-9.12           mvtnorm_1.2-4            
## [123] cli_3.6.5                 compiler_4.4.1           
## [125] rlang_1.1.6               crayon_1.5.3             
## [127] ggsignif_0.6.4            labeling_0.4.3           
## [129] fs_1.6.6                  stringi_1.8.7            
## [131] viridisLite_0.4.2         lazyeval_0.2.2           
## [133] aod_1.3.3                 fontquiver_0.2.1         
## [135] patchwork_1.3.0           hms_1.1.3                
## [137] sparseMatrixStats_1.16.0  gfonts_0.2.0             
## [139] shiny_1.10.0              rbibutils_2.2.16         
## [141] gt_0.10.1                 memoise_2.0.1            
## [143] bslib_0.9.0